DBMS > Atos Standard Common Repository vs. Datomic vs. Heroic vs. TerminusDB

System Properties Comparison Atos Standard Common Repository vs. Datomic vs. Heroic vs. TerminusDB

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

Graph DBMS

Secondary database models

Document store
RDF store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.datomic.com

github.com/spotify/heroic

terminusdb.com

Technical documentation

docs.datomic.com

spotify.github.io/heroic

terminusdb.github.io/terminusdb/#

Developer

Atos Convergence Creators

Cognitect

Spotify

DataChemist Ltd.

Initial release

2016

2012

2014

2018

Current release

1703

1.0.6735, June 2023

11.0.0, January 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache 2.0

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Java, Clojure

Java

Prolog, Rust

Server operating systems

Linux

All OS with a Java VM

Linux

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

Typing

predefined data types such as float or date

optional

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

via Elasticsearch

SQL

Support of SQL

SQL-like query language (WOQL)

APIs and other access methods

LDAP

RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

All languages with LDAP bindings

Clojure
Java

JavaScript
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Triggers

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

But extensive use of caching in the application peers

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

yes

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

in-memory journaling

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

User concepts

Access control

LDAP bind authentication

Role-based access control

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